Cleveland State University

Department of Electrical and Computer Engineering

 

 

EEC442/542 The Art and Science of Feedback Control

 

Understanding the power of an idea that changed the way we live

 

 

Catalog Data:        EEC 442/542 The Art and Science of Feedback Control (4-0-4). Prerequisites: Senior standing in EEC442 and graduate standing in EEC542. This course traces the idea of feedback control throughout history and is made broadly accessible to engineering and science majors alike at both undergraduate and graduate levels. By going back in time and trying to understand the problems that precipitated the great discoveries in controls, we strive to grasp the thought process of the great minds in the history of controls, leading to, hopefully, better understanding and appreciation of the art and science of problem solving in the area of automatic control systems.

 

Reference books: O. Mayr, The Origins of Feedback Control, The MIT Press, 1970

                                N. Wiener, Cybernetics, The MIT Press, 1961

                                W. T. Powers, Living Control Systems, The Control System Group Inc. 1989

                                D. Afolabi, Catastrophes in Control Systems, Darsaki Publications, 2002

                                R. Rosen, Anticipatory Systems, Pergamon Press, 1985

                                J. R. Leigh, Control Theory, 2nd  Edition. Institute of Electrical Engineers, 2004.

                                C. Rohrs, J. Melsa, and D. Schultz, Linear Control Systems, McGraw-Hill, Inc., 1993.

 

Coordinator:          Dr. Zhiqiang Gao, Associate Professor of Electrical Engineering.

 

Goals:                     To understand and appreciate feedback control both as a mechanism in nature and as an artifact everywhere in this increasingly engineered world that we live in.  In particular, this course is designed to help students i) get familiar with important events and figures in the history of controls; ii) review a wide range of control system design problems and solutions; iii) develop skills in understanding and formulating real world control problems, iv) recognize performance limitations due to physical constraints; v) identify uncertainties and nonlinearities in the real world; vi) develop the ability to find the right tool for a given problem; and vii) identify a real world control problem, formulate it, find a solution, and carry out the design, simulation and implementation in a realistic manner.

 

 

Fulfillment of EE and CE Program Objectives and Outcomes (EEC442):

Objectives:

(1) practice electrical engineering

(2) define and diagnose problems, and provide and implement electrical engineering solutions in an industrial environment

 (6) develop their knowledge beyond the undergraduate level and to keep current with advancements in electrical engineering

Outcomes:

(a) an ability to apply knowledge of mathematics, science, and engineering to electrical engineering

(c) an ability to design a system, component, or process to meet desired needs

(e) an ability to identify, formulate, and solve electrical engineering problems

(i) a recognition of the need for, and an ability to engage in life-long learning

(j) a knowledge of contemporary issues

(k) an ability to use the techniques, skills, and modern engineering tools necessary for electrical engineering practice.


Topics                                                                                                                                         Lecture Hours

 

                                                                                                                                                                               

1.        Introduction                                                                                                                                                2

2.        Non-mathematical description of control problems and the role of mathematics                            4

3.        Ancient control systems                                                                                                                          4

4.        Steam Engine, its improvements and the industrial revolution                                                          2

5.        Feedback Amplifier, Bell Labs, and the birth of Cybernetics                                                              4

6.        The making of classical control theory: Bode, Nyquist and other early pioneers                           4

7.        Review of classical control theory                                                                                                          4

8.        Sputnik and the modern control era: Kalman filter                                                                               2

9.        Review of modern control: Optimal, Adaptive, Robust, Intelligent                                                   4

10.     Mathematization of control engineering: not that there is anything wrong with it                         4

11.     An alternative problem formulation: ataraxia-freedom from disturbance                                          2

12.     Poncelet’s Principle: disturbance rejection without feedback                                                            2

13.     Schipanov and invariance principle                                                                                                        2

14.     Han and Active Disturbance Rejection Control                                                                                   4

15.     Recent developments in advanced industrial control                                                                          2

16.     Case Studies: formulation and solutions of real world control problems                                         4

17.     Presentations                                                                                                                                              8

18.     Exam                                                                                                                                                             2

Total                                                                                                                                                                   60

 

 

Design Projects:   Undergraduate and graduate students are required to complete two design projects; graduate students are required to carry out a research project by solving a particular control problem of their choice, write a term paper and make a presentation.

 

Non-Design Projects:

                                Students generally complete at least two non-design projects on history of great                  ideas in controls and on novel applications of control theory in non-engineering fields.                                                                            

 

Computer Usage: Some projects may require the use of Matlab/Simulink.

 

Estimated ABET Category Content: Engineering Topics: 4 credits, or 100%

 

 

Teaching and Learning Methods:

 

                A problem oriented teaching method will be employed to promote active learning on the part of students. Instead of starting with the end results of many years of research and practice, we’ll begin with the problems that puzzled the pioneers of our fields. We’ll study the nature of the problems and the train of thoughts and methodologies that led to the success of the past investigations.  It is in this sense that we gain a historical perspective and some understanding of how those great minds work, helping us, hopefully, to be a more active learner and a creative thinker.

 

About Feedback Control:

               

                Feedback control is an idea that has been discovered and rediscovered throughout human history. Today, it permeates all engineering branches, natural sciences and social sciences. Understanding the essence of this idea and its manifestations in various feedback systems, natural or artificial, allows us to gain deeper insight on how these systems work and, more importantly, to make them work better.

 

 

 

Prepared by Dr. Zhiqiang Gao                                                                                       Date: Sept. 20, 20005

Revised by Dr. Zhiqiang Gao                                                                                             Date: Nov. 3, 2008